Smart Tactile Sensing Systems Based on Embedded CNN Implementations
Embedding machine learning methods into the data decoding units may enable the extraction of complex information making the tactile sensing systems intelligent. This paper presents and compares the implementations of a convolutional neural network model for tactile data decoding on various hardware...
Main Authors: | Mohamad Alameh, Yahya Abbass, Ali Ibrahim, Maurizio Valle |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2020-01-01
|
Series: | Micromachines |
Subjects: | |
Online Access: | https://www.mdpi.com/2072-666X/11/1/103 |
Similar Items
-
Efficient and Small Network Using Multi-Trim Network Structure for Tactile Object Recognition on Embedded Systems
by: Pornthep Sarakon, et al.
Published: (2020-01-01) -
How the Environment Shapes Tactile Sensing: Understanding the Relationship Between Tactile Filters and Surrounding Environment
by: Leone Costi, et al.
Published: (2022-07-01) -
The Design of Intelligent Building Lighting Control System Based on CNN in Embedded Microprocessor
by: Xisheng Ding, et al.
Published: (2023-03-01) -
Approximate Computing Circuits for Embedded Tactile Data Processing
by: Mario Osta, et al.
Published: (2022-01-01) -
Robotic tactile sensing : technologies and system /
by: Ravinder S. Dahiya, et al.
Published: (c201)